In the field of video surveillance, matching data storage capabilities to storage requirements has taken on increased importance with the introduction of high definition and network cameras, among other advances. Towards this end, many challenges arise when attempting to provide sufficient storage to meet demands in a cost effective manner. Namely, in the prior art a trade off always occurs between conserving storage space, and thus costs, and maintaining high quality video.
FIG. 1 illustrates one video surveillance environment 100 in an example of the prior art to explain the aforementioned tradeoff. In FIG. 1, cameras 111, 113, and 115, capture video of scenes 101, 103, and 105 respectively. In this example, each camera transmits the captured video to video storage system 121 at 1.33 units/day. As a result, video storage system 121 receives for storage about 4 units/day of video.
In this example, video storage system 121 has a storage capacity of 16 units. Further in this example, can be assumed for illustrative purposes that video must be retained for 4 days. Thus, at an aggregate rate of 4 units/day, video storage system 121 is capable of storing video for 4 days and any new video can be retained in accordance with requirements. As is shown in FIG. 1, video A contains 4 units of video and is greater than 4 days old. Video A is therefore discarded in some manner, such as by deletion or overwriting, to free up storage capacity for new video F, which is provided to video storage system 121 at a rate of 4 units/day. In the meantime, video B, C, D, and E remains stored in video storage system 121, although it can be understood that as video F arrives, some of video B will be discarded.
Referring now to FIGS. 2A and 2B, two examples 201 and 202 are provided to demonstrate the shortcomings of present video storage systems. Turning first to FIG. 2A, blocks of video A-F are shown with varying levels of quality in example 201. In typical video systems, compression must be varied from time to time in order to maintain a relatively constant data rate. In this example, to maintain a data rate of 1.33 units/day per camera, each camera adjusts compression based on its own individual data rate to generate video within blocks A, C, E, and F that has been compressed to varying degrees.
Unfortunately, the times when compression is increased due to increased activity in the camera view often correlate to periods when the recorded video is most valuable for surveillance purposes. As a result, the recorded, compressed video tends to include artifacts and other markers of low quality. Thus, while in FIG. 2A a video retention requirement may be met by each camera adjusting its own compression levels based on its own individual data rate, the quality of the stored video can be undesirable.
FIG. 2B illustrates a different approach whereby quality is emphasized over retention and bit rates are allowed to vary. In other words, during the times in example 201 when compression would be increased to reduce data rates, in example 202 compression is kept consistently low in order to maintain consistently high quality. This provides for high quality, stored video that is desirable for surveillance purposes. However, this also utilizes a greater amount of storage space. As a result, video is discarded from storage to make room for new video at a rate that does not satisfy retention requirements. For example, in FIG. 2A video block B is shown to have been prematurely discarded, even though it is only 4 days old.
Thus, a vexing tradeoff exists between providing high quality video and yet meeting retention requirements for that video. One solution is to simply add storage to levels exceeding the maximum possible data rate for any group of cameras. However, such a solution would be prohibitively expensive and wasteful. Rather, an elegant and useful solution is desired to achieve the storage of high quality video while meeting retention requirements.